SYSTEM AND METHOD OF CLASSIFYING FINANCIAL TRANSACTIONS BY USAGE PATTERNS OF A USER

1 . A method of classifying financial transactions, comprising:

gathering transaction data from a user's financial account;

extracting metadata from the transaction data in accordance with at least one business rule;

sequentially analyzing the metadata using at least one of a constant-time lookup data structure, a Radix tree, a Lucene tree and a fuzzy logic method until a unique identifier is found that is associated with the metadata;

adding the metadata with the unique identifier to the constant-time lookup data structure; and

classifying the transaction data based on the unique identifier.

2 . The method of claim 1 , wherein the transaction data comprises at least one of a checking transaction, a credit card transaction, a prepaid card transaction, and a bill pay transaction.

3 . The method of claim 1 , wherein the metadata comprises at least one of a merchant, a geographic location, a merchant category, a date and a time.

4 . The method of claim 1 further comprising:

segregating the transaction data into segregated information.

5 . The method of claim 4 , wherein the segregated information comprises at least one of a date of a transaction, an amount of a transaction, a merchant and a geographic location.

6 . The method of claim 4 , wherein preprocessing techniques are used to segregate the transaction data.

7 . The method of claim 6 , wherein the preprocessing techniques comprise at least one processing rule from the group consisting of text transitions between character types and transitions from letters to numbers or delimiting characters.

8 . The method of claim 1 , wherein classifying includes organizing financial transactions to identify financially related usage patterns of the user.

9 . A method of classifying financial transactions, comprising:

gathering transaction data from a user's financial account;

extracting metadata from the transaction data in accordance with at least one business rule;

using a Radix tree to identify a unique identifier associated with the metadata; and

classifying the transaction data based on the unique identifier.

10 . The method of claim 9 further comprising:

using a location Radix tree to identify unique geolocation identifiers; and

using a merchant Radix tree to identify unique merchant identifiers.

11 . A method of classifying financial transactions, comprising:

gathering transaction data from a user's financial account;

extracting metadata from the transaction data in accordance with at least one business rule;

using a Lucene tree to identify a unique identifier associated with the metadata; and

classifying the transaction data based on the unique identifier.

12 . The method of claim 11 further comprising:

using a location Lucene tree to identify unique geolocation identifiers; and

using a merchant Lucene tree to identify unique merchant identifiers.

13 . The method of claim 11 , wherein the associated metadata and unique identifier are used to populate a constant-time lookup data structure.

14 . The method of claim 11 , wherein a partial match in the Lucene tree between the metadata and the unique identifier is compared to a predetermined threshold and if the threshold is exceeded, the unique identifier is associated with the metadata.

15 . The method of claim 11 , wherein the unique identifier comprises at least one of a geographical location, a zipcode, a merchant name, a merchant category and a date.

16 . A method, comprising:

gathering transaction data from a user's financial account;

extracting metadata from the transaction data in accordance with at least one business rule;

using fuzzy logic to identify a unique identifier associated with the metadata; and

classifying the transaction data based on the unique identifier.

17 . The method of claim 16 , wherein the associated metadata and unique identifier are used to populate a constant-time lookup data structure.

18 . The method of claim 16 , wherein a partial match in the fuzzy logic between the metadata and the unique identifier is compared to a predetermined threshold and if the threshold is exceeded, the unique identifier is associated with the metadata.

19 . The method of claim 16 , wherein the unique identifier comprises at least one of a geographical location, a zipcode, a merchant name, a merchant category and a date.